Bayesian calibration of simple forest models with multiplicative mathematical structure: A case study with two Light Use Efficiency models in an alpine forest

Maurizio Bagnara, Marcel Van Oijen, David Cameron, Damiano Gianelle, Federico Magnani and Matteo Sottocornola

Ecological Modelling, 2018, vol. 371, issue C, 90-100

Abstract: Forest models are increasingly being used to study ecosystem functioning, through simulation of carbon fluxes and productivity in different biomes and plant functional types all over the world. Several forest models based on the concept of Light Use Efficiency (LUE) rely mostly on a simplified mathematical structure and empirical parameters, require little amount of data to be run, and their computations are usually fast. However, possible calibration issues must be investigated in order to ensure reliable results.

Keywords: Forest model; Prelued; Bayesian calibration; Markov Chain Monte Carlo; Light Use Efficiency; GPP (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:371:y:2018:i:c:p:90-100

DOI: 10.1016/j.ecolmodel.2018.01.014

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